Abstract A115: Contextual synthetic lethality: Repair-deficient hypoxic tumor cells are sensitized to poly(ADP-ribose) polymerase (PARP) inhibition
Bibliographic record
Abstract
Abstract Acute and chronic hypoxia exists within the 3D microenvironment of solid tumors and drives therapy resistance, genetic instability and metastasis. Replicating cells exposed to either severe acute hypoxia (16 h with 0.02% O2) followed by reoxygenation or moderate chronic hypoxia (72 h with 0.2% O2) treatments had decreased RAD51 protein expression and homologous recombination (HR) function. As HR defects are synthetically lethal with poly(ADP-ribose) polymerase 1 (PARP1) inhibition, we evaluated the sensitivity of HR-defective hypoxic cells to PARP inhibition. Although PARP inhibition did not affect HR, we observed increased clonogenic killing in HR-deficient hypoxic cells following inhibition or siRNA depletion of PARP1. PARP1−/− MEFs showed a proliferative disadvantage and a lack of cell adaption to hypoxia when compared to PARP1+/+ MEFs. PARP-inhibited hypoxic cells accumulated H2AX and 53BP1 foci as a consequence of altered DNA replication firing leading to S phase-specific cell killing. In support of this proposed mode of action, PARP inhibitor treated RKO xenografts showed increased H2AX-positivity and cell death across hypoxic cell gradients in subregions with suppressed RAD51 expression. We conclude that the repair defects observed in hypoxic cells can sensitize hypoxic cells to PARP inhibition as a consequence of microenvironment-mediated “contextual synthetic lethality”. As all solid tumors contain hypoxic cells, this may broaden the clinical utility of PARP inhibition in cancer therapy. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):A115.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".